Voltammetric Data for Cardiac Biomarker Detection Algorithm Validation

An algorithm-assisted framework for automated interpretation of voltammetric data from screen-printed carbon electrode potentiostats. The dataset, created by Wikan Danar Sunindyo and shared on figshare, contains processed electrochemical signals used to identify cardiac troponin. It demonstrates a method employing polynomial fitting and asymmetric least squares for baseline correction and peak detection.

Use Cases

• Benchmark automated peak detection algorithms based on processed voltammetric signals.
• Validate baseline correction methods (polynomial fitting, asymmetric least squares) for cyclic and differential pulse voltammetry.
• Train models to distinguish biomarker concentration levels relative to a predefined detection threshold.
• Compare algorithm performance against reference electrochemical analysis software for reproducibility.

Strengths

• Dataset is shared under a permissive CC-BY-4.0 license.
• The proposed method showed close agreement with reference electrochemical analysis software.
• File size is 5.5 KB, indicating a focused and manageable dataset.

Limitations

• Row count and column-level documentation are unknown, requiring manual inspection after download.
• The dataset's small scale (5.5 KB) limits its scope to a specific methodological validation.

Provenance

Source

figshare

Collection Method

Data likely originates from electrochemical experiments using screen-printed carbon electrode potentiostats.

Freshness

Last updated 2026-05-13 17:49:23; freshness should be verified.